Financial Planning and Services · AI Strategy
A study of where the firm's work gets stuck
Situation
Views on where staff time went, and on which processes caused rework or delay, came from memory and impressions. Choosing what to automate next required firmer evidence drawn from the firm's own work.
Solution
Jeff Hunt studied a year of the firm's day-to-day work and built a map of its activities. The map counted each task once, however people described it. For each activity, the study measured its volume, its complexity, who performed it and how many steps it took. Each activity was then scored as a candidate for automation.
The study also identified where work got stuck, through rework, confusion, escalation or delay. It summarized the recurring causes, each with examples.
Design decisions
By then the firm already had several tools, and the next choices needed to rest on evidence from its own work. Every finding came with examples, so leadership could check it against their own experience before acting on it. The study only read and reported, and it changed nothing in the firm's systems. It also led to the client life change list.
Outcome
Leadership can choose the next automation projects from a scored list drawn from the firm's own work. The recurring causes of rework and delay are written down with examples, so each one can be addressed directly.
